34,349 research outputs found
On Evaluating Commercial Cloud Services: A Systematic Review
Background: Cloud Computing is increasingly booming in industry with many
competing providers and services. Accordingly, evaluation of commercial Cloud
services is necessary. However, the existing evaluation studies are relatively
chaotic. There exists tremendous confusion and gap between practices and theory
about Cloud services evaluation. Aim: To facilitate relieving the
aforementioned chaos, this work aims to synthesize the existing evaluation
implementations to outline the state-of-the-practice and also identify research
opportunities in Cloud services evaluation. Method: Based on a conceptual
evaluation model comprising six steps, the Systematic Literature Review (SLR)
method was employed to collect relevant evidence to investigate the Cloud
services evaluation step by step. Results: This SLR identified 82 relevant
evaluation studies. The overall data collected from these studies essentially
represent the current practical landscape of implementing Cloud services
evaluation, and in turn can be reused to facilitate future evaluation work.
Conclusions: Evaluation of commercial Cloud services has become a world-wide
research topic. Some of the findings of this SLR identify several research gaps
in the area of Cloud services evaluation (e.g., the Elasticity and Security
evaluation of commercial Cloud services could be a long-term challenge), while
some other findings suggest the trend of applying commercial Cloud services
(e.g., compared with PaaS, IaaS seems more suitable for customers and is
particularly important in industry). This SLR study itself also confirms some
previous experiences and reveals new Evidence-Based Software Engineering (EBSE)
lessons
A Programming Environment Evaluation Methodology for Object-Oriented Systems
The object-oriented design strategy as both a problem decomposition and system development paradigm has made impressive inroads into the various areas of the computing sciences. Substantial development productivity improvements have been demonstrated in areas ranging from artificial intelligence to user interface design. However, there has been very little progress in the formal characterization of these productivity improvements and in the identification of the underlying cognitive mechanisms. The development and validation of models and metrics of this sort require large amounts of systematically-gathered structural and productivity data. There has, however, been a notable lack of systematically-gathered information on these development environments. A large part of this problem is attributable to the lack of a systematic programming environment evaluation methodology that is appropriate to the evaluation of object-oriented systems
Technical Debt Prioritization: State of the Art. A Systematic Literature Review
Background. Software companies need to manage and refactor Technical Debt
issues. Therefore, it is necessary to understand if and when refactoring
Technical Debt should be prioritized with respect to developing features or
fixing bugs. Objective. The goal of this study is to investigate the existing
body of knowledge in software engineering to understand what Technical Debt
prioritization approaches have been proposed in research and industry. Method.
We conducted a Systematic Literature Review among 384 unique papers published
until 2018, following a consolidated methodology applied in Software
Engineering. We included 38 primary studies. Results. Different approaches have
been proposed for Technical Debt prioritization, all having different goals and
optimizing on different criteria. The proposed measures capture only a small
part of the plethora of factors used to prioritize Technical Debt qualitatively
in practice. We report an impact map of such factors. However, there is a lack
of empirical and validated set of tools. Conclusion. We observed that technical
Debt prioritization research is preliminary and there is no consensus on what
are the important factors and how to measure them. Consequently, we cannot
consider current research conclusive and in this paper, we outline different
directions for necessary future investigations
Structured Review of Code Clone Literature
This report presents the results of a structured review of code clone literature. The aim of the review is to assemble a conceptual model of clone-related concepts which helps us to reason about clones. This conceptual model unifies clone concepts from a wide range of literature, so that findings about clones can be compared with each other
The Scalability-Efficiency/Maintainability-Portability Trade-off in Simulation Software Engineering: Examples and a Preliminary Systematic Literature Review
Large-scale simulations play a central role in science and the industry.
Several challenges occur when building simulation software, because simulations
require complex software developed in a dynamic construction process. That is
why simulation software engineering (SSE) is emerging lately as a research
focus. The dichotomous trade-off between scalability and efficiency (SE) on the
one hand and maintainability and portability (MP) on the other hand is one of
the core challenges. We report on the SE/MP trade-off in the context of an
ongoing systematic literature review (SLR). After characterizing the issue of
the SE/MP trade-off using two examples from our own research, we (1) review the
33 identified articles that assess the trade-off, (2) summarize the proposed
solutions for the trade-off, and (3) discuss the findings for SSE and future
work. Overall, we see evidence for the SE/MP trade-off and first solution
approaches. However, a strong empirical foundation has yet to be established;
general quantitative metrics and methods supporting software developers in
addressing the trade-off have to be developed. We foresee considerable future
work in SSE across scientific communities.Comment: 9 pages, 2 figures. Accepted for presentation at the Fourth
International Workshop on Software Engineering for High Performance Computing
in Computational Science and Engineering (SEHPCCSE 2016
A survey on software coupling relations and tools
Context
Coupling relations reflect the dependencies between software entities and can be used to assess the quality of a program. For this reason, a vast amount of them has been developed, together with tools to compute their related metrics. However, this makes the coupling measures suitable for a given application challenging to find.
Goals
The first objective of this work is to provide a classification of the different kinds of coupling relations, together with the metrics to measure them. The second consists in presenting an overview of the tools proposed until now by the software engineering academic community to extract these metrics.
Method
This work constitutes a systematic literature review in software engineering. To retrieve the referenced publications, publicly available scientific research databases were used. These sources were queried using keywords inherent to software coupling. We included publications from the period 2002 to 2017 and highly cited earlier publications. A snowballing technique was used to retrieve further related material.
Results
Four groups of coupling relations were found: structural, dynamic, semantic and logical. A fifth set of coupling relations includes approaches too recent to be considered an independent group and measures developed for specific environments. The investigation also retrieved tools that extract the metrics belonging to each coupling group.
Conclusion
This study shows the directions followed by the research on software coupling: e.g., developing metrics for specific environments. Concerning the metric tools, three trends have emerged in recent years: use of visualization techniques, extensibility and scalability. Finally, some coupling metrics applications were presented (e.g., code smell detection), indicating possible future research directions. Public preprint [https://doi.org/10.5281/zenodo.2002001]
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